Table 1.

Selected studies for mobile health technology in primary prevention of cardiovascular disease

Risk factor	Study name/ authors	Study design	Sample size RCT no. enrolled, or sys. review studies included)	Intervention	Outcomes	Findings
Aggregate	Widmer et al. [9]	Systematic review	51 studies	mHealth interventions compared with usual care alone	CVD outcomes, risk factors (BP, lipids, BMI)	Significant reduction in CVD outcomes; concomitant reductions in weight, but not BP
Smoking	Txt2Stop [12]	RCT	5800 enrolled	SMS (regularized behavioral support vs. unrelated messages)	Smoking abstinence (biochemically verified)	Continuous abstinence improved
	OnQ [14]	RCT	3530 enrolled	SMS-based vs. internet-based cessation platform	Smoking abstinence	Improved abstinence compared with control; no difference between SMS and internet
	Taylor et al. [15]	Systematic review (Cochrane)	67 studies	mHealth smoking cessation interventions	Smoking abstinence	Internet-based interventions moderately more effective than passive interventions; no evidence supporting internet over other active strategies (i.e. SMS)
	Whittaker et al. [13]	Systematic review (Cochrane)	5 studies	Interactive smoking cessation apps compared with passive interventions	Smoking abstinence	No evidence supporting interactive apps over passive apps, with very low certainty
	MobileQuit [20]	RCT	1271 enrolled	Combined app-SMS vs. internet-based cessation interventions	Primary: Smoking abstinence Secondary: user satisfaction	Significant improvement in abstinence and satisfaction for app-SMS group compared with internet group
Weight loss	mFit (MyFitnessPal) [21]	RCT	212 enrolled	MyFitnessPal plus usual care vs. usual care alone	Primary: Weight loss Secondary: app satisfaction, app use, SBP	No difference in weight loss; high satisfaction reported; use frequency dropped after first month
	Siopis et al. [25]	Systematic review	14 studies	SMS (variety of weight loss programs with regular SMS communications vs. program without communication)	Weight loss	Text messaging interventions can promote weight loss in short-term, long-term data lacking
	LOSE IT [26]	RCT	196 enrolled	Smartphone-based activity and weight tracking with competitive vs. noncompetitive goal tracking compared with no goal tracking. Also compared EHR-integrated data collection to non-EHR-integrated	Weight loss	Activity and weight goal tracking produces statistically significant weight loss; no difference in competitive vs. noncompetitive arms; no difference in EHR-integrated vs. non-EHR-integrated subgroup
	Senecal et al. [27]	Retrospective observational	250 000 individuals	App-guided weight-loss program with dietary replacement and wireless scale incorporation	Weight loss	Significant short-term and midterm weight loss
Physical inactivity	mActive [23]	RCT	48 enrolled	Smartphone-based activity tracker with smart SMS messages vs. without SMS vs. blinded activity tracking (control)	Mean daily step count	Improved step count with smart SMS and activity tracking; no difference between activity tracking without SMS and control
BP	Tucker et al. [17]	Systematic review	25 studies	BP self-monitoring alone vs. with cointerventions (physician feedback, medication changes, education)	BP control	BP monitoring with cointerventions leads to improved control; self-monitoring alone is not associated with improved control
Lipid control	Akbari et al. [29]	Systematic review	18 studies	mHealth interventions in patients with metabolic syndrome and related disorders	Lipid profile changes	mHealth associated with improved total and LDL cholesterol
Diabetes	Kroger et al. [28]	Retrospective	363 records reviewed	Diabetic self-care and monitoring with CGM devices	A1C reduction	CGM use was associated with a small but statistically significant improvement in A1C control

BP, blood pressure; CGM, continuous glucose monitor; CVD, cardiovascular disease; EHR, Electronic Health Record; mHealth, mobile health technologies; RCT, randomized control trial; SMS, short media service.